DESCRIPTION: A number of validated quality of life (QL) instruments have emerged for use in oncology, but comparability across the most frequently used approaches has not been demonstrated. For health providers and policy makers to review data across trials, standardized measures derived from valid instruments will be necessary. A second issue is that QL methodology is currently dichotomized into two complementary approaches: The psychometric approach with its emphasis on subjective response from the patient perspective and the utility approach with its emphasis on health policy. Both approaches offer essential information, necessitating their integration. The objectives of this proposal are to develop standardized scores for the most common QL instruments (Aim 1) and to evaluate QL in priority trials selected by the QL subcommittee of the Eastern Cooperative Oncology Group (ECOG) (Aim 2). A supplemental objective is to explore the relationship between psychometric and utility approaches to measuring QL. This proposal combines the scientific and administrative resources of five core ECOG institutions (Rush-Presbyterian, Northwestern, Fox Chase, Johns Hopkins, and Medical College of Ohio), with the organizational, data management and statistical resources of the ECOG. It focuses on lung cancer, breast cancer, and AIDS-related malignancies. For Aim 1, interview-generated and questionnaire QL data from a heterogeneous group of 1800 non-ECOG patients will be combined (when necessary) with patient QL data (@ 1,100 patients) from 6 ECOG protocols (2 breast; 2 lung; 2 HIV-related malignancies). Four instruments will be equated. Logit measure total scores of each QL instrument will be tested pairwise for equivalence. Whenever possible, related subtests of different instruments will be tested. In addition, whole test total scores (including those created in consultation with authors of QL scales that do not presently produce a whole test total score) will be tested for equivalence, as will higher order factors determined by structural equation modeling. Assuming equivalence of pairwise comparisons, each scale will be transformed into a common and familiar metric ("Q-score" with mean = 50 and sd = 10) for each equivalent subtest or total score, which is clinically meaningful, sensitive to known differences, and easy to utilize. For Aim 2, the QL data from the 6 protocols will be analyzed according to QL hypotheses specific to each protocol. For the supplemental objective, a utility weight generated by a Time Trade Off (TTO) interview will be compared to QL data generated on the Functional Assessment of Cancer Therapy (FACT) scale (including patient utilities for FACT QL domains). The first comparison will be similar to the Aim 1 approach, and the second will evaluate the significance of parameter estimates which compare unweighted scores to those which have been weighted by individual preferences.